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Neo4j — Northwind Benchmark Report

Run: 2026-05-13T12:51:35.861062-07:00 → 2026-05-13T12:51:46.908517-07:00 Endpoint: bolt://localhost:7687 (database neo4j)

Workload

  • Categories: 96 | Suppliers: 144 | Customers: 1,200
  • Products seeded: 48,000
  • Orders seeded: 48,000 (1..6 lines each)
  • Random seed: 42 (deterministic dataset)
  • Seed nodes: 97,440
  • Seed relationships: 312,050
  • Approx. seed payload (JSON-serialized): 35.4 MiB
  • Seed duration: 5,750.07 ms
  • Iterations per query: 10

Query Latency

Query Mean (ms) Median (ms) P95 (ms) P99 (ms) Min (ms) Max (ms) StdDev (ms) Ops/sec
products_per_category 9.34 8.88 12.82 13.01 7.36 13.06 1.96 106.74
customer_category_distinct_orders 226.67 228.87 259.13 261.76 184.64 262.41 26.98 4.41
optional_match_orders_count 72.58 72.00 84.98 85.57 63.23 85.71 8.41 13.77
revenue_by_product 85.96 84.17 93.62 95.71 80.46 96.23 4.70 11.63
  • Overall mean latency: 98.64 ms
  • Overall throughput: 7.76 ops/sec
  • Total benchmark wall-clock (sampled): 31.630 s

Correctness

Seed counts (from the database's own count(...) queries):

Entity Count
Category 96
Supplier 144
Customer 1,200
Product 48,000
Order 48,000
PART_OF edges 48,000
SUPPLIES edges 48,000
PURCHASED edges 48,000
ORDERS edges 168,050

Per-query result fingerprints (SHA-256 over canonicalised rows):

Query Rows Hash Stable across iterations
products_per_category 96 91e9f1f063680a6d… ✅
customer_category_distinct_orders 10 5da36214d5163220… ✅
optional_match_orders_count 100 8950fcdaab16eaeb… ✅
revenue_by_product 10 60b64c678f4c01fd… ✅

✅ No intra-run correctness errors.

Power Consumption

  • Samples collected: 30 (~1s each)
  • Sampled duration: 30.43 s
  • Avg CPU power: 8,608.1 mW
  • Avg GPU power: 95.4 mW
  • Avg package power: 8,703.5 mW
  • Estimated energy (benchmark window): 264.87 J

Memory Pressure

  • Samples collected: 34 (~1s each)
  • Avg used (active + wired + compressor): 32.5 GiB
  • Peak used: 33.4 GiB
  • Avg free: 12.0 GiB
  • Min free: 10.9 GiB
  • Avg compressed (logical): 17.1 GiB
  • Peak compressed: 17.1 GiB

Storage

  • Raw data files: 50.7 MiB (53,207,040 bytes)
  • Indexes/stats: 7.5 MiB (7,823,360 bytes)
  • Write-ahead logs: 144.4 MiB (151,363,584 bytes)
  • Metadata/bookkeeping: 1.1 MiB (1,191,936 bytes)
  • Preallocated scratch (excluded): 4.0 KiB (4,096 bytes)
  • Unclassified (other): 0 B (0 bytes)
  • Full data directory du: 203.7 MiB (213,590,016 bytes)
  • Classified sum: 203.7 MiB (213,590,016 bytes, Δ vs du = +0 bytes)

Raw-data size is the comparison headline. Preallocated memtable/WAL scratch files (8 MiB memtable on Badger, 1 MiB GC discard log, etc.) are excluded because they hold the same bytes regardless of dataset size.

Top raw-data files | File | Size | |---|---:| | `databases/neo4j/neostore.propertystore.db` | 18.1 MiB | | `databases/neo4j/neostore.propertystore.db.strings` | 14.9 MiB | | `databases/neo4j/neostore.relationshipstore.db` | 10.2 MiB | | `databases/neo4j/neostore.propertystore.db.arrays` | 5.9 MiB | | `databases/neo4j/neostore.nodestore.db` | 1.4 MiB | | `databases/neo4j/neostore.relationshipgroupstore.degrees.db` | 48.0 KiB | | `databases/system/neostore.relationshipgroupstore.degrees.db` | 40.0 KiB | | `databases/neo4j/neostore` | 8.0 KiB | | `databases/neo4j/neostore.labeltokenstore.db.names` | 8.0 KiB | | `databases/neo4j/neostore.relationshiptypestore.db.names` | 8.0 KiB |

Queries

products_per_category

MATCH (c:Category)<-[:PART_OF]-(p:Product)
            RETURN c.categoryName AS categoryName, count(p) AS productCount
            ORDER BY productCount DESC

customer_category_distinct_orders

MATCH (c:Customer)-[:PURCHASED]->(o:Order)-[:ORDERS]->(p:Product)-[:PART_OF]->(cat:Category)
            RETURN c.companyName AS companyName, cat.categoryName AS categoryName, count(DISTINCT o) AS orders
            ORDER BY orders DESC, companyName ASC, categoryName ASC
            LIMIT 10

optional_match_orders_count

MATCH (p:Product)
            OPTIONAL MATCH (p)<-[r:ORDERS]-(o:Order)
            RETURN p.productName AS productName, count(o) AS orderCount
            ORDER BY orderCount DESC, productName ASC
            LIMIT 100

revenue_by_product

MATCH (p:Product)<-[r:ORDERS]-(:Order)
            WITH p, sum(p.unitPrice * r.quantity) AS revenue
            RETURN p.productName AS productName, revenue
            ORDER BY revenue DESC, productName ASC
            LIMIT 10